/**
 * This program is free software, you can redistribute it and/or modify.
 * Copyright (c) 2025 Huawei Technologies Co., Ltd.
 * This file is a part of the CANN Open Software.
 * Licensed under CANN Open Software License Agreement Version 2.0 (the "License").
 * Please refer to the License for details. You may not use this file except in compliance with the License.
 * THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
 * See LICENSE in the root of the software repository for the full text of the License.
 */

#include <unistd.h>
#include <iostream>
#include <vector>
#include "acl/acl.h"
#include "aclnnop/aclnn_max_pool2d_with_indices.h"

#define CHECK_RET(cond, return_expr) \
do {                               \
    if (!(cond)) {                   \
    return_expr;                   \
    }                                \
} while (0)

#define LOG_PRINT(message, ...)     \
do {                              \
    printf(message, ##__VA_ARGS__); \
} while (0)

int64_t GetShapeSize(const std::vector<int64_t>& shape) {
int64_t shapeSize = 1;
for (auto i : shape) {
    shapeSize *= i;
}
return shapeSize;
}

int Init(int32_t deviceId, aclrtStream* stream) {
// 固定写法，资源初始化
auto ret = aclInit(nullptr);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclInit failed. ERROR: %d\n", ret); return ret);
ret = aclrtSetDevice(deviceId);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtSetDevice failed. ERROR: %d\n", ret); return ret);
ret = aclrtCreateStream(stream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtCreateStream failed. ERROR: %d\n", ret); return ret);
return 0;
}

template <typename T>
int CreateAclTensor(const std::vector<T>& hostData, const std::vector<int64_t>& shape, void** deviceAddr,
                    aclDataType dataType, aclTensor** tensor) {
auto size = GetShapeSize(shape) * sizeof(T);
// 调用aclrtMalloc申请Device侧内存
auto ret = aclrtMalloc(deviceAddr, size, ACL_MEM_MALLOC_HUGE_FIRST);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtMalloc failed. ERROR: %d\n", ret); return ret);

// 调用aclrtMemcpy将Host侧数据拷贝到Device侧内存上
ret = aclrtMemcpy(*deviceAddr, size, hostData.data(), size, ACL_MEMCPY_HOST_TO_DEVICE);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtMemcpy failed. ERROR: %d\n", ret); return ret);

// 计算连续tensor的strides
std::vector<int64_t> strides(shape.size(), 1);
for (int64_t i = shape.size() - 2; i >= 0; i--) {
    strides[i] = shape[i + 1] * strides[i + 1];
}

// 调用aclCreateTensor接口创建aclTensor
*tensor = aclCreateTensor(shape.data(), shape.size(), dataType, strides.data(), 0, aclFormat::ACL_FORMAT_NCHW,
                            shape.data(), shape.size(), *deviceAddr);
return 0;
}

int main() {
// 1. （固定写法）device/stream初始化，参考acl API手册
// 根据自己的实际device填写deviceId
int32_t deviceId = 0;
aclrtStream stream;
auto ret = Init(deviceId, &stream);
// check根据自己的需要处理
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("Init acl failed. ERROR: %d\n", ret); return ret);

// 2. 构造输入与输出，需要根据API的接口自定义构造
std::vector<int64_t> selfShape = {1, 1, 4, 3};
std::vector<int64_t> outShape = {1, 1, 2, 1};
std::vector<int64_t> indicesShape = {1, 1, 4, 64};
std::vector<int64_t> kernelSizeData = {2, 2};
std::vector<int64_t> strideData = {2, 2};
std::vector<int64_t> paddingData = {0, 0};
std::vector<int64_t> dilationData = {1, 1};
void* selfDeviceAddr = nullptr;
void* outDeviceAddr = nullptr;
void* indicesDeviceAddr = nullptr;
aclTensor* self = nullptr;
aclTensor* out = nullptr;
aclTensor* indices = nullptr;
std::vector<float> selfHostData = {0.0850, -0.5147, -0.0212, -0.5654, -0.3222, 0.5847, 1.7510, 0.9954, 0.1842, 0.8392, 0.4835, 0.9213};
std::vector<float> outHostData = {0, 0};
std::vector<int8_t> indicesHostData(256, 0);

// 创建self aclTensor
ret = CreateAclTensor(selfHostData, selfShape, &selfDeviceAddr, aclDataType::ACL_FLOAT, &self);
CHECK_RET(ret == ACL_SUCCESS, return ret);
// 创建out aclTensor
ret = CreateAclTensor(outHostData, outShape, &outDeviceAddr, aclDataType::ACL_FLOAT, &out);
CHECK_RET(ret == ACL_SUCCESS, return ret);
// 创建indices aclTensor
ret = CreateAclTensor(indicesHostData, indicesShape, &indicesDeviceAddr, aclDataType::ACL_INT8, &indices);
CHECK_RET(ret == ACL_SUCCESS, return ret);

// 创建输入数组
aclIntArray* kernelSize = aclCreateIntArray(kernelSizeData.data(), 2);
aclIntArray* stride = aclCreateIntArray(strideData.data(), 2);
aclIntArray* padding = aclCreateIntArray(paddingData.data(), 2);
aclIntArray* dilation = aclCreateIntArray(dilationData.data(), 2);
const bool ceilMode = false;

uint64_t workspaceSize = 0;
aclOpExecutor* executor;

// aclnnMaxPool2dWithMask接口调用示例
// 3. 调用CANN算子库API，需要修改为具体的API名称
// 调用aclnnMaxPool2dWithMask第一段接口
ret = aclnnMaxPool2dWithMaskGetWorkspaceSize(self, kernelSize, stride, padding, dilation, ceilMode, out, indices, &workspaceSize, &executor);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnMaxPool2dWithMaskGetWorkspaceSize failed. ERROR: %d\n", ret); return ret);
// 根据第一段接口计算出的workspaceSize申请device内存
void* workspaceAddr = nullptr;
if (workspaceSize > 0) {
    ret = aclrtMalloc(&workspaceAddr, workspaceSize, ACL_MEM_MALLOC_HUGE_FIRST);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("allocate workspace failed. ERROR: %d\n", ret); return ret);
}
// 调用aclnnMaxPool2dWithMask第二段接口
ret = aclnnMaxPool2dWithMask(workspaceAddr, workspaceSize, executor, stream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnMaxPool2dWithMask failed. ERROR: %d\n", ret); return ret);

// 4. （固定写法）同步等待任务执行结束
ret = aclrtSynchronizeStream(stream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtSynchronizeStream failed. ERROR: %d\n", ret); return ret);

// 5. 获取输出的值，将Device侧内存上的结果拷贝至Host侧，需要根据具体API的接口定义修改
auto size = GetShapeSize(outShape);
std::vector<float> resultData(size, 0);
ret = aclrtMemcpy(resultData.data(), resultData.size() * sizeof(resultData[0]), outDeviceAddr,
                    size * sizeof(resultData[0]), ACL_MEMCPY_DEVICE_TO_HOST);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("copy out result from device to host failed. ERROR: %d\n", ret); return ret);
for (int64_t i = 0; i < size; i++) {
    LOG_PRINT("result[%ld] is: %f\n", i, resultData[i]);
}

size = GetShapeSize(indicesShape);
std::vector<int8_t> indicesResultData(size, 0);
ret = aclrtMemcpy(indicesResultData.data(), indicesResultData.size() * sizeof(indicesResultData[0]), indicesDeviceAddr,
                    size * sizeof(indicesResultData[0]), ACL_MEMCPY_DEVICE_TO_HOST);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("copy indices result from device to host failed. ERROR: %d\n", ret); return ret);
for (int64_t i = 0; i < size; i++) {
    LOG_PRINT("result[%ld] is: %d\n", i, indicesResultData[i]);
}

// 6. 释放aclTensor和aclScalar，需要根据具体API的接口定义修改
aclDestroyTensor(self);
aclDestroyTensor(out);
aclDestroyTensor(indices);

// 7. 释放device资源，需要根据具体API的接口定义修改
aclrtFree(selfDeviceAddr);
aclrtFree(outDeviceAddr);
aclrtFree(indicesDeviceAddr);
if (workspaceSize > 0) {
    aclrtFree(workspaceAddr);
}
aclrtDestroyStream(stream);
aclrtResetDevice(deviceId);
aclFinalize();
return 0;
}